Sentiment Analysis for Customer Reviews

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dc.contributor Aalto University en
dc.contributor Aalto-yliopisto fi
dc.contributor.advisor Wallenius, Jyrki
dc.contributor.author Reinikainen, Eevi
dc.date.accessioned 2017-07-04T08:38:27Z
dc.date.available 2017-07-04T08:38:27Z
dc.date.issued 2017
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/27200
dc.description.abstract The purpose of this paper is to introduce how sentiment analysis can be used to analyse customer reviews, and how this information can be utilized in businesses. The topic is a current one since it is the first time in history, there are huge amounts of reviews openly available online. These reviews are proven to be influential in sales, and therefore companies should see them as a valuable information source. Sentiment analysis makes it possible to analyse unstructured data sets to gain valuable insights from customers’ opinions. Literature review and illustrative example will be used to answer the following questions: 1. Why do companies need to monitor and understand what their customers are writing online? 2. How can sentiment analysis be used to analyse customer reviews to understand customer opinions? 3. How can this information be utilised in online business? 4. What are the benefits of the method? 5. What are the limitations of the method? The key findings of this paper are that sentiment analysis creates an opportunity to mine opinions from big unstructured dataset, and these results can be used to support decision making in several business applications. en
dc.format.extent 28
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.title Sentiment Analysis for Customer Reviews en
dc.type G1 Kandidaatintyö fi
dc.contributor.school Kauppakorkeakoulu fi
dc.contributor.school School of Business en
dc.contributor.department Tieto- ja palvelutalouden laitos fi
dc.subject.keyword sentiment analysis en
dc.subject.keyword opinion mining en
dc.subject.keyword customer reviews en
dc.subject.keyword data analysis en
dc.identifier.urn URN:NBN:fi:aalto-201707046234
dc.type.ontasot Bachelor's thesis en
dc.type.ontasot Kandidaatintyö fi
dc.programme Business Technology en


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